Paper i proceeding, 2006

With ever-increasing numbers of cars, traffic congestion on the roads is a very serious economic and environmental problem for our modern society. Existing technologies for traffic monitoring and management require stationary infrastructure. These approaches lack flexibility with respect to system deployment and unpredictable events (e.g., accidents). Moreover, the delivery of traffic reports from radio stations is imprecise and often outdated. In the project AutoNomos we aim at developing a decentralized system for traffic monitoring and managing, based on vehicular ad-hoc networks (VANETs). Our objective is to design a system for traffic forecasting that can deliver faster and more appropriate reactions to unpredictable events. In our design, cars collect traffic information, extract the relevant data, and generate traffic reports. A key concept are so-called Hovering Data Clouds (HDCs), which are based on the insight that many crucial structures in traffic (e.g., traffic jams) lead an existence that is independent of the individual cars they are composed of. The result is an elegant, robust and self-organizing distributed information system. In this paper we demonstrate first experimental results.